Development of an ensemble Kalman filter data assimilation system for the Venusian atmosphere

Abstract

The size and mass of Venus is similar to those of the Earth; however, its atmospheric dynamics are considerably different and they are poorly understood due to limited observations and computational difficulties. Here, we developed a data assimilation system based on the local ensemble transform Kalman filter (LETKF) for a Venusian Atmospheric GCM for the Earth Simulator (VAFES), to make full use of the observational data. To examine the validity of the system, two datasets were assimilated separately into the VAFES forecasts forced with solar heating that excludes the diurnal component Qz; one was created from a VAFES run forced with solar heating that includes the diurnal component Qt, whereas the other was based on observations made by the Venus Monitoring Camera (VMC) onboard the Venus Express. The VAFES-LETKF system rapidly reduced the errors between the analysis and forecasts. In addition, the VAFES-LETKF system successfully reproduced the thermal tide excited by the diurnal component of solar heating, even though the second datasets only included horizontal winds at a single altitude on the dayside with a long interval of approximately one Earth day. This advanced system could be useful in the analysis of future datasets from the Venus Climate Orbiter ‘Akatsuki’.